{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Seaborn Tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Distribution plots\n",
    "\n",
    "- distplot\n",
    "- joinplot\n",
    "- pairplot\n",
    "\n",
    "Practise problem on IRIS Dataset\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=sns.load_dataset(\"tips\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlation with Heatmap\n",
    "\n",
    " A correlation heatmap uses colored cells, typically in a monochromatic scale, to show a 2D correlation matrix (table) between two discrete dimensions or event types.\n",
    " It is very important in Feature Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>total_bill</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.675734</td>\n",
       "      <td>0.598315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tip</th>\n",
       "      <td>0.675734</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.489299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <td>0.598315</td>\n",
       "      <td>0.489299</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            total_bill       tip      size\n",
       "total_bill    1.000000  0.675734  0.598315\n",
       "tip           0.675734  1.000000  0.489299\n",
       "size          0.598315  0.489299  1.000000"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d290442e8>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## JoinPlot\n",
    "\n",
    "A join plot allows to study the relationship between 2 numeric variables. The central chart display their correlation. It is usually a scatterplot, a hexbin plot, a 2D histogram or a 2D density plot\n",
    "### Univariate Analysis\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x26d26549048>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='tip',y='total_bill',data=df,kind='hex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x26d268a2780>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='tip',y='total_bill',data=df,kind='reg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pair plot\n",
    "\n",
    "A “pairs plot” is also known as a scatterplot, in which one variable in the same data row is matched with another variable's value, like this: Pairs plots are just elaborations on this, showing all variables paired with all the other variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x26d24010630>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x26d24c41438>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 612.625x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df,hue='sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dist plot\n",
    "\n",
    "Dist plot helps us to check the distribution of the columns feature\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\krish.naik\\AppData\\Local\\Continuum\\anaconda3\\envs\\myenv\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d24a32be0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['tip'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d24aec668>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['tip'],kde=False,bins=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical Plots\n",
    "\n",
    "Seaborn also helps us in doing the analysis on Categorical Data points. In this section we will discuss about\n",
    "\n",
    "- boxplot\n",
    "- violinplot\n",
    "- countplot\n",
    "- bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d286c44e0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Count plot\n",
    "\n",
    "sns.countplot('sex',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d286fa048>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Count plot\n",
    "\n",
    "sns.countplot(y='sex',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\krish.naik\\AppData\\Local\\Continuum\\anaconda3\\envs\\myenv\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d28766668>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Bar plot\n",
    "sns.barplot(x='total_bill',y='sex',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d287ad860>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Bar plot\n",
    "sns.barplot(x='sex',y='total_bill',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Box plot\n",
    "\n",
    "A box and whisker plot (sometimes called a boxplot) is a graph that presents information from a five-number summary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d287f7d30>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot('smoker','total_bill', data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d2885f940>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=\"day\", y=\"total_bill\", data=df,palette='rainbow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d28b23748>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=df,orient='v')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d28c6ecf8>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# categorize my data based on some other categories\n",
    "\n",
    "sns.boxplot(x=\"total_bill\", y=\"day\", hue=\"smoker\",data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Violin Plot\n",
    "\n",
    "Violin plot helps us to see both the distribution of data in terms of Kernel density estimation and the box plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x26d28d5ca20>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=\"total_bill\", y=\"day\", data=df,palette='rainbow')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Practise Homework\n",
    "\n",
    "iris = sns.load_dataset('iris')"
   ]
  },
  {
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